Coronary artery disease is one of the most common causes of sudden death. This disease tends to narrow the lumen of coronary arteries due to arterial wall plaque progression or plaque rupture. This narrowing or stenosis results in the flow of blood through a coronary artery to become obstructed or partially obstructed. Coronary artery stenosis may be treated by medication or by surgical intervention. In one surgical procedure, a fine metallic mesh called a stent is implanted in an affected artery wall and expanded in order to open the narrowed lumen and restore the blood flow. The procedure is typically performed under the guidance of X-ray fluoroscopy which delivers real time video of the clinical tools and devices in the patient's anatomy. Briefly, a metallic guide-wire is first introduced inside the affected artery in order to serve as support for sliding an angioplasty balloon equipped with a stent. In order to visually assess the location of the balloon/stent on the guide-wire, the guide-wire is equipped with two highly radio-opaque markers or marker-balls delimiting the position and extent of the devices. This is described in more detail in an article by V. Bismuth, R. Vaillant, F. Funck, N. Guillard, and L. Najman, entitled, “A comprehensive study of stent visualization enhancement in X-ray images by image processing means”, Medical Image Analysis. vol. 15, no. 4, pp. 565-576, August 2011. FIG. 1 depicts a typical X-ray image of an artery with a guide-wire 10, two markers-balls 12, and a respective stent 14 between the two balls 12. It is clear that accurate assessment of the anatomical location of the stent deployment in relation to the artery vessel walls is key to the success of the procedure and the safety of the patient.
Image processing techniques for X-ray fluoroscopy images are routinely employed to enhance stent visibility and visualization and, thus, support such accurate assessments. Assuming that the stent is well aligned throughout the sequence of images, integrating a sequence of non-contrast stent images to produce a single stent image (via image processing techniques) can effectively improve the contrast and the signal-to-noise ratio (SNR) of the respective stent image. However, in coronary artery intervention, the coronary arteries undergo constant movement and motion correction of their images is nearly always required. Moreover, motion correction of the coronary artery images becomes imperative for aligning a temporal series of stent images to ensure the quality of the enhanced stent image. It is therefore advantageous to have an image processing method that is particularly effective for the alignment of stent images and that, ultimately, provides stent image quality enhancement.